Evidence map›Paper›PMID 41568159›Full record

ArticleThe breast journal2026

Tyrer-Cuzick Lifetime Risk Is Not Associated With Non-BRCA1/2 Pathogenic Variants for Breast Carcinoma.

Divya Rao, Chloe Wernecke, Lisa Baron, Steven Cai, Peter Beitsch, Rakesh Patel, Pat Whitworth, Barry Rosen, Nhan Nguyen Tran, Kevin Hughes and 1 more

Abstract read
In one paragraph

Article in The breast journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Divya RaoDepartment of Emergency Medicine, Nassau University Medical Center, East Meadow, New York, USA, nuhealth.net.ORCID 0009-0001-7036-3080
Chloe WerneckeTargeted Medical Education, Dallas, Texas, USA.
Lisa BaronDepartment of Surgery, Lenox Hill Hospital, Northwell Health, New York, New York, USA, northwell.edu.
Steven CaiDepartment of Surgery, Lenox Hill Hospital, Northwell Health, New York, New York, USA, northwell.edu.
Peter BeitschTargeted Medical Education, Dallas, Texas, USA.
Rakesh PatelTargeted Medical Education, Dallas, Texas, USA.
Pat WhitworthTargeted Medical Education, Dallas, Texas, USA.
Barry RosenTargeted Medical Education, Dallas, Texas, USA.
Nhan Nguyen TranDepartment of Surgery, Lenox Hill Hospital, Northwell Health, New York, New York, USA, northwell.edu.
Kevin HughesDepartment of Surgery, Medical University of South Carolina, Charleston, South Carolina, USA, musc.edu.
Paul L BaronDepartment of Surgery, Lenox Hill Hospital, Northwell Health, New York, New York, USA, northwell.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The Tyrer-Cuzick (TC) or IBIS risk calculator is a widely used tool to estimate the probability of developing breast cancer. The latest version incorporates various factors to assess the risk of breast cancer, including family history, personal history, breast density, and past medical history. The TC is commonly used to guide patients toward further diagnostic imaging, genetic testing, chemoprevention, or risk-reducing surgery. However, it is unclear whether the TC is associated with non-BRCA1/2 pathogenic variants (PVs) in breast cancer susceptibility genes. Methods: A population of 964 patients with TC was evaluated for 12 PVs and variants of unknown significance (VUS) using lab-agnostic genetic testing. Patients were enrolled from 2019 to 2022. Historical TC were used for the subgroup of patients who developed breast cancer after enrollment. TC scores were compared between the three patient cohorts that had BRCA gene mutations, non-BRCA PVs, and negative for PVs, using the Kruskal-Wallis test followed by pairwise comparison using DSCF adjustment for multiple comparisons. Data collection for patient cohorts occurred simultaneously and was only separated in analysis. Logistic regression was carried out to predict BRCA versus negative in a model with TC scores, as well as non-BRCA versus negative. Area under the receiver operating characteristic (ROC) curve (AUC) was calculated to assess model fit. Results: This study found an average TC of 7.71%. A family history of cancer was noted in 78.30% of patients, and a personal history of cancer other than breast occurred in 20.74% of patients. The presence of PVs and VUS was evaluated, and 12.03% of patients were found to have a PV, with an average TC of 8.98%. The most common PVs were CHEK2, BRCA2, BRCA1, and BARD1. Out of those with PVs, 52% had non-BRCA1/2 PVs with an average TC of 5.47%. A total of 102 patients (10.58%) had a VUS, with an average TC of 8.29%. In further statistical analysis, TC were distributed significantly differently among the three groups, with differences observed between the BRCA group and negative group, as well as between BRCA and non-BRCA1/2 PVs group. A higher TC was also associated with BRCA1/BRCA2 variants compared to non-BRCA1/2 PVs. Conclusion: TC scores provide valuable information regarding the lifetime risk of an individual of developing breast cancer. However, the study found they were not associated with prediction of non-BRCA1/2 PVs. When choosing a genetic testing panel for breast cancer genes, TC is not as a reliable predictor on individual patient's family history, NCCN guidelines, or ASBrS guidelines. Our study supports the need to develop a genetic risk calculator that incorporates the predictive value for these non-BRCA1/2 PVs in otherwise low or average TC women.

Indexed as

Breast NeoplasmsAdultAgedBRCA1 ProteinFemaleGenes, BRCA1Genetic Predisposition to DiseaseGenetic TestingHumansMiddle AgedRisk AssessmentBRCA1 Proteinbreast cancerrisk modelTyrer–Cuzick

Identifiers

PMID41568159
PMCPMC12816757

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.